Detection and prediction of real-world severe asthma phenotypes by application of machine learning to electronic health records

Detection and prediction of real-world severe asthma phenotypes by application of machine learning to electronic health records

Background: Asthma is a heterogeneous disease with a diverse array of phenotypes that differ in inflammatory characteristics and severity. Identifying and classifying phenotypes in the real world could provide a foundation to improve and personalize asthma management. Leveraging machine learning in...

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Main Authors: Mehmet Furkan Bağcı, MSc, Toan Do, MD, Samantha R. Spierling Bagsic, PhD, Rahul F. Gomez, MD, Judy H. Jun, MD, Anna L. Ritko, MA, MPhil, Sally E. Wenzel, MD, Truong Nguyen, PhD, Yusuf Öztürk, PhD, Brian D. Modena, MD, MSc
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Journal of Allergy and Clinical Immunology: Global
Subjects:
Asthma
machine learning
electronic health records
predictive modeling
Online Access:http://www.sciencedirect.com/science/article/pii/S2772829325000748
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